2019
DOI: 10.3171/2018.12.spine181397
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Machine learning for automated 3-dimensional segmentation of the spine and suggested placement of pedicle screws based on intraoperative cone-beam computer tomography

Abstract: OBJECTIVEThe goal of this study was to develop and validate a system for automatic segmentation of the spine, pedicle identification, and screw path suggestion for use with an intraoperative 3D surgical navigation system.METHODSCone-beam CT (CBCT) images of the spines of 21 cadavers were obtained. An automated model-based approach was used for segmentation. Using machine learning methodology, the algorithm… Show more

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Cited by 56 publications
(59 citation statements)
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“…Pedicle screw paths were planned using an augmented reality surgical navigation (ARSN) system, as previously described in the literature [23]. Accordingly, a cone beam computed tomography (CBCT) acquisition was performed and used for automatic spine segmentation and creation of a 3D-model of the spine [24]. Based on this 3D-model, using the system's surgical navigation software, pedicle screws were purposefully planned to result in either lateral, inferior, anterior, or medial breach.…”
Section: Surgical Setupmentioning
confidence: 99%
“…Pedicle screw paths were planned using an augmented reality surgical navigation (ARSN) system, as previously described in the literature [23]. Accordingly, a cone beam computed tomography (CBCT) acquisition was performed and used for automatic spine segmentation and creation of a 3D-model of the spine [24]. Based on this 3D-model, using the system's surgical navigation software, pedicle screws were purposefully planned to result in either lateral, inferior, anterior, or medial breach.…”
Section: Surgical Setupmentioning
confidence: 99%
“…Image fusion on endoscopic views for endonasal skull-base surgery Using augmented reality for surgical navigation has several potential benefits compared to conventional navigation with display of 2D medical imaging on a separate screen. Overlaying segmented anatomical structures from CT or MRI on the endoscopic video stream enables navigation without the use of dedicated instruments and thereby improves workflow, while visualizing sub-surface anatomy [48]. However, it has been shown that although users of AR navigation were able to identify a target more accurately, they were at the same time at risk of inattentional blindness, e.g.…”
Section: Discussionmentioning
confidence: 99%
“…to evaluate tumor resection grade or intraoperative changes of anatomy. Fast and accurate segmentation of CBCT images has been performed successfully intraoperatively in the system's spine surgery application [48].…”
Section: Discussionmentioning
confidence: 99%
“…After exposure of the spine, adhesive skin markers were placed for patient tracking and a 3D cone beam CT (CBCT) was performed to image the region that required spinal instrumentation. Planning of pedicle screw trajectories was performed based on the CBCT images and automatic spine segmentation 10 . The screws were one by one activated in the software.…”
Section: Methodsmentioning
confidence: 99%